A Novel Criterion for Characterizing Diffusion Anisotropy in HARDI Data Based on the MDL Technique

Huaizhong Zhang, T.M McGinnity, S.A Coleman, M Jing

Research output: Chapter in Book/Report/Conference proceedingConference proceeding (ISBN)


Based on the spherical harmonic decomposition of HARDI data, we propose a new criterion for characterizing the diffusion anisotropy in a voxel directly from the SH coefficients. Essentially, by considering the Rician noise in diffusion data, we modify the Rissanen’s criterion for fitting the diffusion situation in a voxel. In addition, the minimum description length (MDL) criterion has been employed for interpreting information from both the SH coefficients and the data. The criterion obtained can make use of the diffusion information so as to efficiently separate the different diffusion distributions. Various synthetic datasets have been used for verifying our method. The experimental results show the performance of the proposed criterion is accurate.
Original languageEnglish
Title of host publicationNot Known
Publication statusPublished - 2010
EventInternational Conference on Medical Biometrics (ICMB) - Hong Kong, China
Duration: 28 Jun 201030 Jun 2010


ConferenceInternational Conference on Medical Biometrics (ICMB)
CityHong Kong


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